
Vibing @Lynxjs_org · ⚛️ Former @Reactjs, @ReactNative, @HermesEngine · 👨🔬 λ.TaPL/FP/@TC39/@W3C
NYC · CA · China
Joined September 2013
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Xuan Huang · 黄玄 retweeted
Playing a round of tile matching game in Midscene with Jev 1.4’s new vision capabilities.
Planning averages just 0.4s per call, and model fees are about $0.006 for the whole game.
Midscene, an AI E2E automation framework built around vision.
Not gonna lie we have @LynxJS_org + OpenUI surfaces running in production already. It's awesome!
For 30 years, technology has moved in one direction: turning information into intuitive interfaces
Somehow, the smartest software we’ve ever built took us back to a textbox
We’ve spent the last 2 years at @openuidev trying to fix that. 6 months ago we open-sourced it: 10K+ GitHub stars, 6M+ downloads
ChatGPT shipped Intelligent UI and showed everyone what it looks like
Today we’re releasing OpenUI 1.0 bringing it to every other agent
Yeah, AI is eating frontend. But isn't it eating backend too?
Genuinely curious:
What’s the real moat for backend engineers now?
Which backend skills are still worth learning deeply?
Sorry, but Claude is still so much better than GPT.
(Not just because Claude gave me another six months and Codex didn’t.)
Xuan Huang · 黄玄 retweeted
Announcing Apex: agentic coding model for mobile and web, specialized in React.
We built Apex from a single idea: can an open-weight model deliver frontier-level performance at lower cost?
Yes. Apex is SOTA in React Native and Next.js.
Try it now: apex.callstack.com
Congrats to the launch!
Gotta try that with Lynx as well
Introducing e2e
The agentic testing framework for any app
~/ npx e2e init
→ Fully Open Source
→ Mix deterministic and agentic APIs
→ Supports web, mobile, and more
→ Bring your own agent and infrastructure
→ Run locally or in CI
tester.army/e2e
Preact 11 is awesome. It adds modern React features such as use and forwarded ref, while preserving a lean and even performant foundation that we can build our own dual-threaded model upon at Lynx.
Is “vibe formal” a thing now? Not sure if I feel more or less valuable as someone who used to major in formal verification.
I used Opus 5.5 to formally verify the Claude Agent SDK using Lean. A couple short prompts = 16 PRs fixing various bugs and race conditions. Video attached.
TLA+ also works well. I sometimes combine Lean and TLA+ to look for issues around data flow, concurrency, and state mgmt.
I don't know either language well, but Claude is excellent at both. This approach is super useful for formally modeling your code and finding bugs that a human probably wouldn't have spotted.
Is formal verification the future of coding (or at least, bug finding)?
I should probably let AI finish my thesis:
scholar.google.com/citations…






















